Analyzing Rental Property Deals with Claude Cowork

For the active real estate investor, "deal flow" is a double-edged sword. You need to see a hundred deals to buy one, but analyzing a hundred deals takes time you don't have. The result is often "analysis paralysis" or, worse, missed opportunities because you couldn't underwrite a deal fast enough.

Claude Cowork changes the velocity of this pipeline. Instead of manually typing numbers from a PDF into a spreadsheet, you can use Cowork to perform the initial underwriting autonomously. This allows you to discard the 95% of bad deals in minutes and focus your deep work on the top 5%.

This guide details a professional workflow for automated deal screening.

The Problem: The "Pro Forma" Gap

Sellers maximize pro formas. Buyers need actuals. The time-consuming part of analysis is not the math; it's normalizing the data—stripping out the broker's optimistic "Year 1 Market Rent" assumptions and replacing them with your own conservative criteria.

Cowork excels here because it can read the PDF text and understand your logical instructions for adjustment.

Phase 1: The Intake & Standardization

Create a folder named Inbound_Deals. Drop the Offering Memorandums (OMs) or flyers for the week into it.

The "Screener" Prompt:

"I have uploaded 5 PDFs for multifamily properties in the 'Inbound_Deals' folder.
Create a standardized summary table in Excel (Deal_Screen_v1.xlsx).
For each property, extract:

1. Asking Price
2. Gross Scheduled Income (Current)
3. Gross Scheduled Income (Pro Forma/Market)
4. Total Expenses (Use the broker's number, but flag if it is less than 35% of GSI)
5. Net Operating Income (NOI)

Add a calculated column for 'Entry Cap Rate' (NOI / Asking Price). Filter out any deal where the Entry Cap Rate is below 5.5%."

The Insight: Notice the instruction to "flag if expenses < 35%." This uses Cowork as a logic engine, not just a copier. It helps you instantly spot unrealistic expense ratios.

Phase 2: The "Back of the Napkin" Math

Once you have a single target property, you need to apply your specific financing assumptions to see if the equity returns work.

The "Cash-on-Cash" Prompt:

"Focus on 123_Main_Street.pdf. Build a simple 5-year cash flow model in Excel.
Assumptions to use:

• Down Payment: 25%
• Interest Rate: 6.75% (amortized over 30 years)
• Vacancy Rate: Hardcode at 8%
• Property Management: 10% of Effective Gross Income
• Rent Growth: 2% per year
• Expense Growth: 3% per year

Calculate the Cash-on-Cash Return for Year 1 and the Debt Service Coverage Ratio (DSCR). If DSCR is below 1.25x, highlight the cell in red."

This turns a static PDF into a dynamic model that reflects your lending environment, not the seller's.

Phase 3: Stress Testing

The market is volatile. A good investor asks, "What happens if I'm wrong?"

The "Sensitivity Analysis" Prompt:

"Update the Excel model to include a sensitivity data table.
Show how the Year 1 Cash-on-Cash Return changes based on two variables:

1. Interest Rate (Range: 6.0% to 8.0% in 0.5% increments)
2. Vacancy Rate (Range: 5% to 15% in 2.5% increments)

Generate a short text summary interpreting the table. At what interest rate does the deal become cash flow negative?"

Phase 4: The Location Context

Numbers don't exist in a vacuum. If you have market reports or comparable sales data in your folder, Cowork can synthesize them.

The "Market Check" Prompt:

"Read the 'Market_Report_Q1_2026.pdf' in the parent folder.
Compare the 'Average Rent per Unit' in the subject property (123_Main_Street.pdf) to the average vintage-adjusted rents for that submarket listed in the report. Is the subject property under-rented or over-rented compared to the market average?"

Conclusion

By using Claude Cowork, you shift your role from "Data Entry Clerk" to "Portfolio Manager." You spend zero time finding the property tax line item in a messy PDF and all your time deciding if the risk-adjusted return fits your thesis.